Jia Qinggang, Zhang Tiankui, Zhang Fengna, et al. Development of Monte Carlo code for Z-pinch driven fusion neutron imaging diagnosis system simulation[J]. High Power Laser and Particle Beams, 2013, 25: 177-181. doi: 10.3788/HPLPB20132501.0177
Citation:
Jia Qinggang, Zhang Tiankui, Zhang Fengna, et al. Development of Monte Carlo code for Z-pinch driven fusion neutron imaging diagnosis system simulation[J]. High Power Laser and Particle Beams, 2013, 25: 177-181. doi: 10.3788/HPLPB20132501.0177
Jia Qinggang, Zhang Tiankui, Zhang Fengna, et al. Development of Monte Carlo code for Z-pinch driven fusion neutron imaging diagnosis system simulation[J]. High Power Laser and Particle Beams, 2013, 25: 177-181. doi: 10.3788/HPLPB20132501.0177
Citation:
Jia Qinggang, Zhang Tiankui, Zhang Fengna, et al. Development of Monte Carlo code for Z-pinch driven fusion neutron imaging diagnosis system simulation[J]. High Power Laser and Particle Beams, 2013, 25: 177-181. doi: 10.3788/HPLPB20132501.0177
The model of Z-pinch driven fusion imaging diagnosis system was set up by a Monte Carlo code based on the Geant4 simulation toolkit. All physical processes that the reality involves are taken into consideration in simulation. The light image of low neutron yield (about 1010) pill was obtained. Three types of image reconstruction algorithm, i.e. Richardson-Lucy, Wiener filtering and genetic algorithm were employed to reconstruct the neutron image with a low signal to noise ratio (SNR) and yield. The effects of neutron yields and the SNR on reconstruction performance were discussed. The results show that genetic algorithm is very robust for reconstructing neutron images with a low SNR. And the index of reconstruction performance and the image correlation coefficient using genetic algorithm, are proportional to the SNR of the neutron coded image.